https://www.ft.com/content/5ff6469a-6dd8-11ea-89df-41bea055720b
If the results are confirmed, they imply that fewer than one in a thousand of those infected with Covid-19 become ill enough to need hospital treatment, said Sunetra Gupta, professor of theoretical epidemiology, who led the study. The vast majority develop very mild symptoms or none at all.
The research presents a very different view of the epidemic to the modelling at Imperial College London, which has strongly influenced government policy. “I am surprised that there has been such unqualified acceptance of the Imperial model,” said Prof Gupta.
The modelling brings back into focus “herd immunity”, the idea that the virus will stop spreading when enough people have become resistant to it because they have already been infected. The government abandoned its unofficial herd immunity strategy — allowing controlled spread of infection — after its scientific advisers said this would swamp the National Health Service with critically ill patients.
New epidemiological model suggests the vast majority of people suffer little or no illness
If the results are confirmed, they imply that fewer than one in a thousand of those infected with Covid-19 become ill enough to need hospital treatment, said Sunetra Gupta, professor of theoretical epidemiology, who led the study. The vast majority develop very mild symptoms or none at all.
The research presents a very different view of the epidemic to the modelling at Imperial College London, which has strongly influenced government policy. “I am surprised that there has been such unqualified acceptance of the Imperial model,” said Prof Gupta.
The modelling brings back into focus “herd immunity”, the idea that the virus will stop spreading when enough people have become resistant to it because they have already been infected. The government abandoned its unofficial herd immunity strategy — allowing controlled spread of infection — after its scientific advisers said this would swamp the National Health Service with critically ill patients.
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